fix some bug of mask in fastspeech

examples/fastspeech/synthesis.py

@@ -18,6 +18,7 @@ import argparse
 from parse import add_config_options_to_parser
 from pprint import pprint
 from ruamel import yaml
+from matplotlib import cm
 import numpy as np
 import paddle.fluid as fluid
 import paddle.fluid.dygraph as dg
@@ -64,8 +65,7 @@ def synthesis(text_input, args):
         pos_text = np.arange(1, text.shape[1] + 1)
         pos_text = np.expand_dims(pos_text, axis=0)
         enc_non_pad_mask = get_non_pad_mask(pos_text).astype(np.float32)
-        enc_slf_attn_mask = get_attn_key_pad_mask(pos_text,
-                                                  text).astype(np.float32)
+        enc_slf_attn_mask = get_attn_key_pad_mask(pos_text).astype(np.float32)
 
         text = dg.to_variable(text)
         pos_text = dg.to_variable(pos_text)
@@ -101,8 +101,17 @@ def synthesis(text_input, args):
             do_trim_silence=False,
             sound_norm=False)
 
+        np.save('mel_output', mel_output_postnet.numpy())
         mel_output_postnet = fluid.layers.transpose(
             fluid.layers.squeeze(mel_output_postnet, [0]), [1, 0])
+        x = np.uint8(cm.viridis(mel_output_postnet.numpy()) * 255)
+        writer.add_image('mel_0_0', x, 0, dataformats="HWC")
+        ground_truth = _ljspeech_processor.load_wav(
+            str('/paddle/Parakeet/dataset/LJSpeech-1.1/wavs/LJ001-0175.wav'))
+        ground_truth = _ljspeech_processor.melspectrogram(ground_truth).astype(
+            np.float32)
+        x = np.uint8(cm.viridis(ground_truth) * 255)
+        writer.add_image('mel_gt_0', x, 0, dataformats="HWC")
         wav = _ljspeech_processor.inv_melspectrogram(mel_output_postnet.numpy(
         ))
         writer.add_audio(text_input, wav, 0, cfg['audio']['sr'])
@@ -114,4 +123,5 @@ if __name__ == '__main__':
     parser = argparse.ArgumentParser(description="Train Fastspeech model")
     add_config_options_to_parser(parser)
     args = parser.parse_args()
-    synthesis("Transformer model is so fast!", args)
+    synthesis("Simple as this proposition is, it is necessary to be stated,",
+              args)

examples/fastspeech/synthesis.sh

@@ -4,7 +4,7 @@ python -u synthesis.py \
 --use_gpu=1 \
 --alpha=1.0 \
 --checkpoint_path='checkpoint/' \
---fastspeech_step=71000 \
+--fastspeech_step=89000 \
 --log_dir='./log' \
 --config_path='configs/synthesis.yaml' \
 

parakeet/models/fastspeech/decoder.py

@@ -88,7 +88,8 @@ class Decoder(dg.Layer):
             dec_slf_attn_list (list[Variable]): len(n_layers), the decoder self attention list.
         """
         dec_slf_attn_list = []
-        slf_attn_mask = layers.expand(slf_attn_mask, [self.n_head, 1, 1])
+        if slf_attn_mask:
+            slf_attn_mask = layers.expand(slf_attn_mask, [self.n_head, 1, 1])
 
         # -- Forward
         dec_output = enc_seq + self.position_enc(enc_pos)

parakeet/models/fastspeech/fastspeech.py

@@ -142,6 +142,7 @@ class FastSpeech(dg.Layer):
                 encoder_output, alpha=alpha)
             slf_attn_mask = get_triu_tensor(
                 decoder_pos.numpy(), decoder_pos.numpy()).astype(np.float32)
+            slf_attn_mask = np.expand_dims(slf_attn_mask, axis=0)
             slf_attn_mask = fluid.layers.cast(
                 dg.to_variable(slf_attn_mask == 0), np.float32)
             slf_attn_mask = dg.to_variable(slf_attn_mask)

parakeet/models/transformer_tts/decoder.py

@@ -149,6 +149,7 @@ class Decoder(dg.Layer):
             zero_mask = layers.expand(zero_mask, [self.num_head, 1, 1])
 
         else:
+            mask = layers.expand(mask, [self.num_head, 1, 1])
             m_mask, m_self_mask, zero_mask = None, None, None
 
         # Decoder pre-network